The Netflix Experience : Reshaping the Creative Process: Cultural Co-Production of Content: A user-focus approach to recommendation algorithms

Abstract: This project proposes a user-focused approach to study the algorithm logic of on-demand apps, using Netflix as a case study. The main research interest is the perception that the user has about the suggestion and recommendation logic of Netflix. In order to gather the information, a walkthrough method on Netflix was applied as well as personal, in-depth think aloud interviews were carried out. The sample consisted on a selection of heavy users, millennials ex-pats living in Singapore and working in the creative industry to get specific insights on their relationship with the algorithm.  To analyze the gathered material, qualitative content analysis was carried out. This kind of study is important within today’s contemporary media environment to have integral approach to users perceptions instead of just analytical figures and numbers. The theoretical context used to enlight some of the conclusions discussed on this research were based on the study of media in everyday life, global cultural industry studies, as well as algorithm culture and the science and technology studies. How algorithms are perceived have major repercussions not only on on-demand apps, technology business models or entertainment industry but also an intense influence on the way people consume content. Re-thinking the user as a co-producer of information and knowledge, considering some of the implications this phenomenon might have on the creative industry and how that affects on our daily life are some of the issues this research elaborated on. It can be said that the selected sample appreciates the suggestion logics and it has multiple functionalities: recommendation, curation, entertainment, companionship and leisure. Netflix Originals are very well validated; being one of the main attractions of the app. Interface, functionality and features are also items that the sample positively highlights. The accuracy perception of the algorithm is good, although low when compared to other countries where the sample used the app. The same applies to the amount of content and titles available, being these last two, issues that Netflix could improve.   This research was conducted for 8 months, from October 2016 to May 2017, for Sodertorn University – Stockholm, Sweden, with the guidance and support of Associate Professor Anne Kaun.